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Diffstat (limited to 'src/silx/gui/plot/tools/profile/core.py')
-rw-r--r-- | src/silx/gui/plot/tools/profile/core.py | 525 |
1 files changed, 525 insertions, 0 deletions
diff --git a/src/silx/gui/plot/tools/profile/core.py b/src/silx/gui/plot/tools/profile/core.py new file mode 100644 index 0000000..200f5cf --- /dev/null +++ b/src/silx/gui/plot/tools/profile/core.py @@ -0,0 +1,525 @@ +# coding: utf-8 +# /*########################################################################## +# +# Copyright (c) 2018-2020 European Synchrotron Radiation Facility +# +# Permission is hereby granted, free of charge, to any person obtaining a copy +# of this software and associated documentation files (the "Software"), to deal +# in the Software without restriction, including without limitation the rights +# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +# copies of the Software, and to permit persons to whom the Software is +# furnished to do so, subject to the following conditions: +# +# The above copyright notice and this permission notice shall be included in +# all copies or substantial portions of the Software. +# +# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. +# +# ###########################################################################*/ +"""This module define core objects for profile tools. +""" + +__authors__ = ["V.A. Sole", "T. Vincent", "P. Knobel", "H. Payno", "V. Valls"] +__license__ = "MIT" +__date__ = "17/04/2020" + +import collections +import numpy +import weakref + +from silx.image.bilinear import BilinearImage +from silx.gui import qt + + +CurveProfileData = collections.namedtuple( + 'CurveProfileData', [ + "coords", + "profile", + "title", + "xLabel", + "yLabel", + ]) + +RgbaProfileData = collections.namedtuple( + 'RgbaProfileData', [ + "coords", + "profile", + "profile_r", + "profile_g", + "profile_b", + "profile_a", + "title", + "xLabel", + "yLabel", + ]) + +ImageProfileData = collections.namedtuple( + 'ImageProfileData', [ + 'coords', + 'profile', + 'title', + 'xLabel', + 'yLabel', + 'colormap', + ]) + + +class ProfileRoiMixIn: + """Base mix-in for ROI which can be used to select a profile. + + This mix-in have to be applied to a :class:`~silx.gui.plot.items.roi.RegionOfInterest` + in order to be usable by a :class:`~silx.gui.plot.tools.profile.manager.ProfileManager`. + """ + + ITEM_KIND = None + """Define the plot item which can be used with this profile ROI""" + + sigProfilePropertyChanged = qt.Signal() + """Emitted when a property of this profile have changed""" + + sigPlotItemChanged = qt.Signal() + """Emitted when the plot item linked to this profile have changed""" + + def __init__(self, parent=None): + self.__profileWindow = None + self.__profileManager = None + self.__plotItem = None + self.setName("Profile") + self.setEditable(True) + self.setSelectable(True) + + def invalidateProfile(self): + """Must be called by the implementation when the profile have to be + recomputed.""" + profileManager = self.getProfileManager() + if profileManager is not None: + profileManager.requestUpdateProfile(self) + + def invalidateProperties(self): + """Must be called when a property of the profile have changed.""" + self.sigProfilePropertyChanged.emit() + + def _setPlotItem(self, plotItem): + """Specify the plot item to use with this profile + + :param `~silx.gui.plot.items.item.Item` plotItem: A plot item + """ + previousPlotItem = self.getPlotItem() + if previousPlotItem is plotItem: + return + self.__plotItem = weakref.ref(plotItem) + self.sigPlotItemChanged.emit() + + def getPlotItem(self): + """Returns the plot item used by this profile + + :rtype: `~silx.gui.plot.items.item.Item` + """ + if self.__plotItem is None: + return None + plotItem = self.__plotItem() + if plotItem is None: + self.__plotItem = None + return plotItem + + def _setProfileManager(self, profileManager): + self.__profileManager = profileManager + + def getProfileManager(self): + """ + Returns the profile manager connected to this ROI. + + :rtype: ~silx.gui.plot.tools.profile.manager.ProfileManager + """ + return self.__profileManager + + def getProfileWindow(self): + """ + Returns the windows associated to this ROI, else None. + + :rtype: ProfileWindow + """ + return self.__profileWindow + + def setProfileWindow(self, profileWindow): + """ + Associate a window to this ROI. Can be None. + + :param ProfileWindow profileWindow: A main window + to display the profile. + """ + if profileWindow is self.__profileWindow: + return + if self.__profileWindow is not None: + self.__profileWindow.sigClose.disconnect(self.__profileWindowAboutToClose) + self.__profileWindow.setRoiProfile(None) + self.__profileWindow = profileWindow + if self.__profileWindow is not None: + self.__profileWindow.sigClose.connect(self.__profileWindowAboutToClose) + self.__profileWindow.setRoiProfile(self) + + def __profileWindowAboutToClose(self): + profileManager = self.getProfileManager() + roiManager = profileManager.getRoiManager() + try: + roiManager.removeRoi(self) + except ValueError: + pass + + def computeProfile(self, item): + """ + Compute the profile which will be displayed. + + This method is not called from the main Qt thread, but from a thread + pool. + + :param ~silx.gui.plot.items.Item item: A plot item + :rtype: Union[CurveProfileData,ImageProfileData] + """ + raise NotImplementedError() + + +def _alignedFullProfile(data, origin, scale, position, roiWidth, axis, method): + """Get a profile along one axis on a stack of images + + :param numpy.ndarray data: 3D volume (stack of 2D images) + The first dimension is the image index. + :param origin: Origin of image in plot (ox, oy) + :param scale: Scale of image in plot (sx, sy) + :param float position: Position of profile line in plot coords + on the axis orthogonal to the profile direction. + :param int roiWidth: Width of the profile in image pixels. + :param int axis: 0 for horizontal profile, 1 for vertical. + :param str method: method to compute the profile. Can be 'mean' or 'sum' or + 'none' + :return: profile image + effective ROI area corners in plot coords + """ + assert axis in (0, 1) + assert len(data.shape) == 3 + assert method in ('mean', 'sum', 'none') + + # Convert from plot to image coords + imgPos = int((position - origin[1 - axis]) / scale[1 - axis]) + + if axis == 1: # Vertical profile + # Transpose image to always do a horizontal profile + data = numpy.transpose(data, (0, 2, 1)) + + nimages, height, width = data.shape + + roiWidth = min(height, roiWidth) # Clip roi width to image size + + # Get [start, end[ coords of the roi in the data + start = int(int(imgPos) + 0.5 - roiWidth / 2.) + start = min(max(0, start), height - roiWidth) + end = start + roiWidth + + if method == 'none': + profile = None + else: + if start < height and end > 0: + if method == 'mean': + fct = numpy.mean + elif method == 'sum': + fct = numpy.sum + else: + raise ValueError('method not managed') + profile = fct(data[:, max(0, start):min(end, height), :], axis=1).astype(numpy.float32) + else: + profile = numpy.zeros((nimages, width), dtype=numpy.float32) + + # Compute effective ROI in plot coords + profileBounds = numpy.array( + (0, width, width, 0), + dtype=numpy.float32) * scale[axis] + origin[axis] + roiBounds = numpy.array( + (start, start, end, end), + dtype=numpy.float32) * scale[1 - axis] + origin[1 - axis] + + if axis == 0: # Horizontal profile + area = profileBounds, roiBounds + else: # vertical profile + area = roiBounds, profileBounds + + return profile, area + + +def _alignedPartialProfile(data, rowRange, colRange, axis, method): + """Mean of a rectangular region (ROI) of a stack of images + along a given axis. + + Returned values and all parameters are in image coordinates. + + :param numpy.ndarray data: 3D volume (stack of 2D images) + The first dimension is the image index. + :param rowRange: [min, max[ of ROI rows (upper bound excluded). + :type rowRange: 2-tuple of int (min, max) with min < max + :param colRange: [min, max[ of ROI columns (upper bound excluded). + :type colRange: 2-tuple of int (min, max) with min < max + :param int axis: The axis along which to take the profile of the ROI. + 0: Sum rows along columns. + 1: Sum columns along rows. + :param str method: method to compute the profile. Can be 'mean' or 'sum' + :return: Profile image along the ROI as the mean of the intersection + of the ROI and the image. + """ + assert axis in (0, 1) + assert len(data.shape) == 3 + assert rowRange[0] < rowRange[1] + assert colRange[0] < colRange[1] + assert method in ('mean', 'sum') + + nimages, height, width = data.shape + + # Range aligned with the integration direction + profileRange = colRange if axis == 0 else rowRange + + profileLength = abs(profileRange[1] - profileRange[0]) + + # Subset of the image to use as intersection of ROI and image + rowStart = min(max(0, rowRange[0]), height) + rowEnd = min(max(0, rowRange[1]), height) + colStart = min(max(0, colRange[0]), width) + colEnd = min(max(0, colRange[1]), width) + + if method == 'mean': + _fct = numpy.mean + elif method == 'sum': + _fct = numpy.sum + else: + raise ValueError('method not managed') + + imgProfile = _fct(data[:, rowStart:rowEnd, colStart:colEnd], axis=axis + 1, + dtype=numpy.float32) + + # Profile including out of bound area + profile = numpy.zeros((nimages, profileLength), dtype=numpy.float32) + + # Place imgProfile in full profile + offset = - min(0, profileRange[0]) + profile[:, offset:offset + imgProfile.shape[1]] = imgProfile + + return profile + + +def createProfile(roiInfo, currentData, origin, scale, lineWidth, method): + """Create the profile line for the the given image. + + :param roiInfo: information about the ROI: start point, end point and + type ("X", "Y", "D") + :param numpy.ndarray currentData: the 2D image or the 3D stack of images + on which we compute the profile. + :param origin: (ox, oy) the offset from origin + :type origin: 2-tuple of float + :param scale: (sx, sy) the scale to use + :type scale: 2-tuple of float + :param int lineWidth: width of the profile line + :param str method: method to compute the profile. Can be 'mean' or 'sum' + or 'none': to compute everything except the profile + :return: `coords, profile, area, profileName, xLabel`, where: + - coords is the X coordinate to use to display the profile + - profile is a 2D array of the profiles of the stack of images. + For a single image, the profile is a curve, so this parameter + has a shape *(1, len(curve))* + - area is a tuple of two 1D arrays with 4 values each. They represent + the effective ROI area corners in plot coords. + - profileName is a string describing the ROI, meant to be used as + title of the profile plot + - xLabel the label for X in the profile window + + :rtype: tuple(ndarray,ndarray,(ndarray,ndarray),str) + """ + if currentData is None or roiInfo is None or lineWidth is None: + raise ValueError("createProfile called with invalide arguments") + + # force 3D data (stack of images) + if len(currentData.shape) == 2: + currentData3D = currentData.reshape((1,) + currentData.shape) + elif len(currentData.shape) == 3: + currentData3D = currentData + + roiWidth = max(1, lineWidth) + roiStart, roiEnd, lineProjectionMode = roiInfo + + if lineProjectionMode == 'X': # Horizontal profile on the whole image + profile, area = _alignedFullProfile(currentData3D, + origin, scale, + roiStart[1], roiWidth, + axis=0, + method=method) + + if method == 'none': + coords = None + else: + coords = numpy.arange(len(profile[0]), dtype=numpy.float32) + coords = coords * scale[0] + origin[0] + + yMin, yMax = min(area[1]), max(area[1]) - 1 + if roiWidth <= 1: + profileName = '{ylabel} = %g' % yMin + else: + profileName = '{ylabel} = [%g, %g]' % (yMin, yMax) + xLabel = '{xlabel}' + + elif lineProjectionMode == 'Y': # Vertical profile on the whole image + profile, area = _alignedFullProfile(currentData3D, + origin, scale, + roiStart[0], roiWidth, + axis=1, + method=method) + + if method == 'none': + coords = None + else: + coords = numpy.arange(len(profile[0]), dtype=numpy.float32) + coords = coords * scale[1] + origin[1] + + xMin, xMax = min(area[0]), max(area[0]) - 1 + if roiWidth <= 1: + profileName = '{xlabel} = %g' % xMin + else: + profileName = '{xlabel} = [%g, %g]' % (xMin, xMax) + xLabel = '{ylabel}' + + else: # Free line profile + + # Convert start and end points in image coords as (row, col) + startPt = ((roiStart[1] - origin[1]) / scale[1], + (roiStart[0] - origin[0]) / scale[0]) + endPt = ((roiEnd[1] - origin[1]) / scale[1], + (roiEnd[0] - origin[0]) / scale[0]) + + if (int(startPt[0]) == int(endPt[0]) or + int(startPt[1]) == int(endPt[1])): + # Profile is aligned with one of the axes + + # Convert to int + startPt = int(startPt[0]), int(startPt[1]) + endPt = int(endPt[0]), int(endPt[1]) + + # Ensure startPt <= endPt + if startPt[0] > endPt[0] or startPt[1] > endPt[1]: + startPt, endPt = endPt, startPt + + if startPt[0] == endPt[0]: # Row aligned + rowRange = (int(startPt[0] + 0.5 - 0.5 * roiWidth), + int(startPt[0] + 0.5 + 0.5 * roiWidth)) + colRange = startPt[1], endPt[1] + 1 + if method == 'none': + profile = None + else: + profile = _alignedPartialProfile(currentData3D, + rowRange, colRange, + axis=0, + method=method) + + else: # Column aligned + rowRange = startPt[0], endPt[0] + 1 + colRange = (int(startPt[1] + 0.5 - 0.5 * roiWidth), + int(startPt[1] + 0.5 + 0.5 * roiWidth)) + if method == 'none': + profile = None + else: + profile = _alignedPartialProfile(currentData3D, + rowRange, colRange, + axis=1, + method=method) + # Convert ranges to plot coords to draw ROI area + area = ( + numpy.array( + (colRange[0], colRange[1], colRange[1], colRange[0]), + dtype=numpy.float32) * scale[0] + origin[0], + numpy.array( + (rowRange[0], rowRange[0], rowRange[1], rowRange[1]), + dtype=numpy.float32) * scale[1] + origin[1]) + + else: # General case: use bilinear interpolation + + # Ensure startPt <= endPt + if (startPt[1] > endPt[1] or ( + startPt[1] == endPt[1] and startPt[0] > endPt[0])): + startPt, endPt = endPt, startPt + + if method == 'none': + profile = None + else: + profile = [] + for slice_idx in range(currentData3D.shape[0]): + bilinear = BilinearImage(currentData3D[slice_idx, :, :]) + + profile.append(bilinear.profile_line( + (startPt[0] - 0.5, startPt[1] - 0.5), + (endPt[0] - 0.5, endPt[1] - 0.5), + roiWidth, + method=method)) + profile = numpy.array(profile) + + # Extend ROI with half a pixel on each end, and + # Convert back to plot coords (x, y) + length = numpy.sqrt((endPt[0] - startPt[0]) ** 2 + + (endPt[1] - startPt[1]) ** 2) + dRow = (endPt[0] - startPt[0]) / length + dCol = (endPt[1] - startPt[1]) / length + + # Extend ROI with half a pixel on each end + roiStartPt = startPt[0] - 0.5 * dRow, startPt[1] - 0.5 * dCol + roiEndPt = endPt[0] + 0.5 * dRow, endPt[1] + 0.5 * dCol + + # Rotate deltas by 90 degrees to apply line width + dRow, dCol = dCol, -dRow + + area = ( + numpy.array((roiStartPt[1] - 0.5 * roiWidth * dCol, + roiStartPt[1] + 0.5 * roiWidth * dCol, + roiEndPt[1] + 0.5 * roiWidth * dCol, + roiEndPt[1] - 0.5 * roiWidth * dCol), + dtype=numpy.float32) * scale[0] + origin[0], + numpy.array((roiStartPt[0] - 0.5 * roiWidth * dRow, + roiStartPt[0] + 0.5 * roiWidth * dRow, + roiEndPt[0] + 0.5 * roiWidth * dRow, + roiEndPt[0] - 0.5 * roiWidth * dRow), + dtype=numpy.float32) * scale[1] + origin[1]) + + # Convert start and end points back to plot coords + y0 = startPt[0] * scale[1] + origin[1] + x0 = startPt[1] * scale[0] + origin[0] + y1 = endPt[0] * scale[1] + origin[1] + x1 = endPt[1] * scale[0] + origin[0] + + if startPt[1] == endPt[1]: + profileName = '{xlabel} = %g; {ylabel} = [%g, %g]' % (x0, y0, y1) + if method == 'none': + coords = None + else: + coords = numpy.arange(len(profile[0]), dtype=numpy.float32) + coords = coords * scale[1] + y0 + xLabel = '{ylabel}' + + elif startPt[0] == endPt[0]: + profileName = '{ylabel} = %g; {xlabel} = [%g, %g]' % (y0, x0, x1) + if method == 'none': + coords = None + else: + coords = numpy.arange(len(profile[0]), dtype=numpy.float32) + coords = coords * scale[0] + x0 + xLabel = '{xlabel}' + + else: + m = (y1 - y0) / (x1 - x0) + b = y0 - m * x0 + profileName = '{ylabel} = %g * {xlabel} %+g' % (m, b) + if method == 'none': + coords = None + else: + coords = numpy.linspace(x0, x1, len(profile[0]), + endpoint=True, + dtype=numpy.float32) + xLabel = '{xlabel}' + + return coords, profile, area, profileName, xLabel |